Artificial intelligence (AI) has the potential to simplify the complexity of the poultry gut microbiome, allowing producers to optimize flock performance and health.
The poultry gut microbiota contains more than 800 identified bacterial species and a large number of as yet unclassified bacterial species. It plays an important role in poultry development but is notoriously difficult to correlate with production outcomes due to its complexity.
The poultry gut microbiota is a relatively new concept. Analyzing its contents provides insight into how feed additives, other nutrients, and management practices can positively or negatively impact poultry flock health, helping producers optimize diets to improve growth rates, reproduction, and overall performance.
Breed differences, temperature fluctuations, heat stress, feed composition, and environmental factors all influence microbiome composition, creating analytical challenges that challenge traditional research methods.
“Scientists typically say it's very difficult to correlate performance and the microbiome because of its complexity,” said Luisa Jean, Galleon technical director. Cargill. “The advantage of AI is that it can analyze large datasets and correlate them.”
This feature enables innovative applications. AI-powered analysis can identify specific biomarkers associated with performance and predict the presence of pathogens. Salmonella and campylobacter — Up to 90% accuracy based solely on microbiome composition.
This technology has analyzed more than 70,000 microbiome samples worldwide, including more than 7,000 from poultry farms.
Revealing the “characteristics of the microbiome”
Practical application is surprisingly simple. Producers collect non-invasive cloacal swabs from approximately 24 birds per farm at strategic ages. The swab is placed in a tube containing a denaturing solution and DNA extraction begins immediately, eliminating the risk of contamination during transport and the need for refrigeration.
Jean explained that AI reveals unique “microbiome signatures” in response to a variety of scenarios, from unexplained mortality to poor litter quality to suboptimal feed conversion rates. Each farm has a unique microbiome profile, allowing for customized nutritional and management interventions.
“We know that a balanced microbiome reduces the risk of infection and the risk of developing disease,” Jean says. The key to AI success is database size. Larger datasets yield more accurate pattern recognition and actionable insights that are simply not possible with traditional analysis methods.
